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Topic Archives: Time Use

Spend Thanksgiving Day with BLS!

Thanksgiving is right around the corner. As we start to think about how we will celebrate, it might be hard to imagine the ties between BLS statistics and celebrating Thanksgiving. So, here’s a short tour of a typical Thanksgiving Day as seen through a few BLS statistics. Enjoy!

9:00 a.m. Put the turkey in the oven

All good chefs know the key to a successful Thanksgiving feast is to get the turkey in the oven bright and early. Whether you are roasting your turkey or firing up a deep fryer in the driveway, you will have to pay more for the fuel. The Consumer Price Index for household energy was pretty stable through 2019 and the first half of 2020 but then started a steady rise in September 2020.

Consumer Price Index for household energy, 2019–21

Editor’s note: Data for this chart are available in the table below.

10:00 a.m. Watch the Macy’s Thanksgiving Day parade

The COVID-19 pandemic has caused ups and downs in the labor market, much like the impact of a windy day for the famous balloons in Macy’s Thanksgiving Day Parade. Keeping with the department store theme, employment in department stores plunged 25.3 percent in April 2020 but then rose 14.1 percent June 2020. These gyrations were more dramatic than the broader retail trade sector.

Monthly percent change in employment in retail trade and department stores, 2019–21

Editor’s note: Data for this chart are available in the table below.

2:00 p.m. Scope out Black Friday deals

After watching the parade, it’s time to plan our Black Friday shopping! As consumers, we are always trying to get more for less. In the retail trade industry, it turns out they are doing just that. The industry has produced more output with steady or decreasing hours worked. The result is a corresponding increase in labor productivity. Now, only if we could prepare a bigger Thanksgiving feast in less time!

Indexes for labor productivity, hours worked, and output in retail trade, 2007–20

Editor’s note: Data for this chart are available in the table below.

4:00 p.m. Play touch football

We need to make some room of the feast we are about to enjoy, so we assemble willing participants and play some touch football in the yard. The American Time Use Survey is the best source of information on how Americans spend their time each day. In this case, let’s compare how much time people spend playing sports versus how much time they spend watching sports on TV. We’ll look only at time spent in these activities on weekend days and holidays. The survey does not have details on what people watch on TV, but we can assume some time reported here is spent watching sports.

Average hours spent watching TV and playing sports, weekend days and holidays, 2019

Editor’s note: Data for this chart are available in the table below.

We can see that Americans, on average, easily spend more time watching TV—3.36 hours—than playing sports—0.34 hours. But what is more interesting is that, on average, those who watch TV watch about 24 percent more than the overall population. However, those who play sports play, on average, nearly 6 times as many hours as the average for the population.

6:00 p.m. Thanksgiving feast

No matter what is on your dinner table this Thanksgiving, chances are it will cost more than previous years. All six major grocery store food groups in the Consumer Price Index for food at home continued to rise sharply in October 2021. Even if you decide to order out, it will set you back a bit more this year. Both full-service meals and limited services meals rose nearly 1 percent in October 2021.

Consumer Price Indexes for food at home and food away from home, 2018–21

Editor’s note: Data for this chart are available in the table below.

7:00 p.m. Watch football

Now that we’ve finished our delicious feast, it’s a time-honored tradition to watch a bit of football on TV. If you are buying a new TV for this holiday, you can expect to pay a bit more. After years of steady declines, import prices for television and video receivers have reversed trend in 2021, much like a wide receiver changing direction to find an opening and catch a game-winning touchdown pass!

Import price index for television and video receivers, 2011–21

Editor’s note: Data for this chart are available in the table below.

9:00 p.m. Say goodbye

It’s hard to say goodbye to your friends and family. In the United States, however, the Job Openings and Labor Turnover Survey is showing that workers are saying goodbye to their employers more often these days. The number of quits has been rising steadily since the shock of the pandemic affected layoffs and discharges in early 2020. (It’s only a coincidence that the layoffs line in the chart below looks like the outline of a pilgrim’s hat.)

Quits, layoffs and discharges, and other job separations, 2019–21

Editor’s note: Data for this chart are available in the table below.

Now we’ve come to the end of our Thanksgiving feast of BLS data. Our hunger for the premier statistics on the U.S. labor force, prices, and productivity, has been satisfied, and we can rest easily knowing there’s a stat for that!

Consumer Price Index for household energy
MonthIndex

Jan 2019

100.000

Feb 2019

99.662

Mar 2019

100.046

Apr 2019

99.952

May 2019

99.679

Jun 2019

99.258

Jul 2019

99.415

Aug 2019

99.253

Sep 2019

99.033

Oct 2019

99.756

Nov 2019

99.890

Dec 2019

99.716

Jan 2020

99.666

Feb 2020

99.355

Mar 2020

98.812

Apr 2020

98.492

May 2020

98.278

Jun 2020

98.501

Jul 2020

98.542

Aug 2020

98.478

Sep 2020

99.590

Oct 2020

100.103

Nov 2020

101.043

Dec 2020

101.377

Jan 2021

101.299

Feb 2021

102.681

Mar 2021

103.436

Apr 2021

104.748

May 2021

105.512

Jun 2021

105.840

Jul 2021

106.664

Aug 2021

107.833

Sep 2021

109.273

Oct 2021

112.872
Monthly percent change in employment in retail trade and department stores
MonthRetail tradeDepartment stores

Jan 2019

-0.1%0.2%

Feb 2019

-0.2-1.4

Mar 2019

-0.1-0.6

Apr 2019

-0.1-0.9

May 2019

-0.1-0.5

Jun 2019

-0.1-0.7

Jul 2019

0.0-0.9

Aug 2019

-0.1-1.4

Sep 2019

0.10.3

Oct 2019

0.20.0

Nov 2019

-0.20.4

Dec 2019

0.3-0.4

Jan 2020

-0.1-2.7

Feb 2020

0.00.3

Mar 2020

-0.8-0.6

Apr 2020

-14.5-25.3

May 2020

3.16.7

Jun 2020

6.314.1

Jul 2020

1.74.3

Aug 2020

1.72.3

Sep 2020

0.2-0.8

Oct 2020

0.70.2

Nov 2020

0.00.7

Dec 2020

0.2-0.6

Jan 2021

0.1-0.3

Feb 2021

0.10.5

Mar 2021

0.30.1

Apr 2021

-0.10.2

May 2021

0.40.9

Jun 2021

0.61.3

Jul 2021

0.00.3

Aug 2021

0.1-0.5

Sep 2021

0.40.5

Oct 2021

0.2-0.2
Indexes for labor productivity, hours worked, and output in retail trade
YearLabor productivityHours workedOutput

2007

100.000100.000100.000

2008

97.76597.65895.475

2009

98.29492.03290.461

2010

100.69492.66793.310

2011

101.39794.68696.008

2012

103.65595.67399.170

2013

108.08095.212102.905

2014

109.91997.268106.916

2015

113.48698.821112.148

2016

118.52598.636116.908

2017

120.71999.896120.593

2018

124.39399.783124.123

2019

130.36098.139127.934

2020

140.39294.650132.880
Average hours spent watching TV and playing sports, weekend days and holidays, 2019
ActivityHours

Watching TV (average of population)

3.36

Watching TV (average of those who watched TV)

4.17

Playing sports (average of population)

0.34

Playing sports (average of those who played sports)

1.94
Consumer Price Indexes for food at home and food away from home
MonthFood at homeFood away from home

Jan 2018

100.000100.000

Feb 2018

99.793100.243

Mar 2018

99.780100.352

Apr 2018

100.026100.594

May 2018

99.779100.929

Jun 2018

99.865101.113

Jul 2018

100.127101.229

Aug 2018

100.198101.421

Sep 2018

100.252101.645

Oct 2018

100.046101.738

Nov 2018

100.259102.029

Dec 2018

100.554102.437

Jan 2019

100.683102.789

Feb 2019

101.014103.153

Mar 2019

101.163103.342

Apr 2019

100.716103.676

May 2019

100.913103.894

Jun 2019

100.718104.232

Jul 2019

100.716104.443

Aug 2019

100.654104.669

Sep 2019

100.902104.940

Oct 2019

101.124105.139

Nov 2019

101.324105.310

Dec 2019

101.331105.611

Jan 2020

101.440106.000

Feb 2020

101.851106.236

Mar 2020

102.220106.395

Apr 2020

104.775106.550

May 2020

105.718106.942

Jun 2020

106.309107.496

Jul 2020

105.343108.002

Aug 2020

105.322108.309

Sep 2020

105.051108.911

Oct 2020

105.177109.210

Nov 2020

105.012109.342

Dec 2020

105.335109.751

Jan 2021

105.203110.122

Feb 2021

105.474110.180

Mar 2021

105.587110.311

Apr 2021

106.047110.649

May 2021

106.423111.258

Jun 2021

107.309112.047

Jul 2021

108.031112.923

Aug 2021

108.431113.405

Sep 2021

109.779114.013

Oct 2021

110.841114.965
Import price index for television and video receivers
MonthIndex

Jan 2011

100.000

Feb 2011

100.173

Mar 2011

100.173

Apr 2011

99.136

May 2011

98.964

Jun 2011

97.409

Jul 2011

97.064

Aug 2011

96.373

Sep 2011

95.855

Oct 2011

94.991

Nov 2011

93.092

Dec 2011

94.128

Jan 2012

94.819

Feb 2012

94.473

Mar 2012

93.955

Apr 2012

92.573

May 2012

92.573

Jun 2012

92.401

Jul 2012

92.401

Aug 2012

92.573

Sep 2012

92.228

Oct 2012

92.573

Nov 2012

90.155

Dec 2012

90.155

Jan 2013

89.810

Feb 2013

89.637

Mar 2013

88.256

Apr 2013

88.083

May 2013

87.910

Jun 2013

87.910

Jul 2013

87.392

Aug 2013

87.219

Sep 2013

85.838

Oct 2013

85.492

Nov 2013

85.492

Dec 2013

85.492

Jan 2014

85.320

Feb 2014

85.320

Mar 2014

85.147

Apr 2014

84.801

May 2014

84.283

Jun 2014

84.111

Jul 2014

83.074

Aug 2014

82.902

Sep 2014

83.074

Oct 2014

81.865

Nov 2014

81.865

Dec 2014

81.347

Jan 2015

79.965

Feb 2015

79.965

Mar 2015

79.965

Apr 2015

79.965

May 2015

79.620

Jun 2015

79.620

Jul 2015

79.620

Aug 2015

79.620

Sep 2015

79.620

Oct 2015

79.447

Nov 2015

79.275

Dec 2015

78.929

Jan 2016

78.756

Feb 2016

77.547

Mar 2016

77.375

Apr 2016

77.029

May 2016

76.857

Jun 2016

77.029

Jul 2016

76.857

Aug 2016

76.684

Sep 2016

76.684

Oct 2016

76.684

Nov 2016

76.684

Dec 2016

76.684

Jan 2017

76.166

Feb 2017

76.166

Mar 2017

75.820

Apr 2017

75.993

May 2017

75.993

Jun 2017

75.993

Jul 2017

75.993

Aug 2017

75.993

Sep 2017

75.820

Oct 2017

75.475

Nov 2017

75.302

Dec 2017

75.130

Jan 2018

75.130

Feb 2018

75.302

Mar 2018

74.784

Apr 2018

74.439

May 2018

74.266

Jun 2018

73.575

Jul 2018

72.884

Aug 2018

72.884

Sep 2018

72.712

Oct 2018

72.539

Nov 2018

72.366

Dec 2018

72.021

Jan 2019

71.330

Feb 2019

70.812

Mar 2019

70.466

Apr 2019

70.466

May 2019

70.294

Jun 2019

69.948

Jul 2019

69.775

Aug 2019

69.603

Sep 2019

69.603

Oct 2019

69.430

Nov 2019

69.085

Dec 2019

68.912

Jan 2020

69.430

Feb 2020

68.048

Mar 2020

67.358

Apr 2020

66.839

May 2020

66.667

Jun 2020

66.667

Jul 2020

66.494

Aug 2020

66.494

Sep 2020

66.321

Oct 2020

66.667

Nov 2020

67.358

Dec 2020

68.048

Jan 2021

68.739

Feb 2021

68.739

Mar 2021

68.566

Apr 2021

69.775

May 2021

70.639

Jun 2021

70.812

Jul 2021

73.402

Aug 2021

73.402

Sep 2021

74.439

Oct 2021

74.784
Quits, layoffs and discharges, and other job separations
MonthQuitsLayoffs and dischargesOther separations

Jan 2019

3,521,0001,689,000301,000

Feb 2019

3,543,0001,769,000353,000

Mar 2019

3,524,0001,721,000331,000

Apr 2019

3,494,0001,954,000313,000

May 2019

3,487,0001,776,000307,000

Jun 2019

3,527,0001,771,000316,000

Jul 2019

3,627,0001,826,000344,000

Aug 2019

3,591,0001,825,000306,000

Sep 2019

3,449,0001,982,000345,000

Oct 2019

3,414,0001,793,000359,000

Nov 2019

3,482,0001,788,000374,000

Dec 2019

3,487,0001,952,000354,000

Jan 2020

3,568,0001,788,000358,000

Feb 2020

3,430,0001,953,000332,000

Mar 2020

2,902,00013,046,000360,000

Apr 2020

2,107,0009,307,000368,000

May 2020

2,206,0002,096,000316,000

Jun 2020

2,646,0002,204,000331,000

Jul 2020

3,182,0001,845,000365,000

Aug 2020

2,987,0001,573,000342,000

Sep 2020

3,307,0001,555,000373,000

Oct 2020

3,352,0001,728,000347,000

Nov 2020

3,296,0002,123,000325,000

Dec 2020

3,407,0001,823,000352,000

Jan 2021

3,306,0001,724,000294,000

Feb 2021

3,383,0001,723,000323,000

Mar 2021

3,568,0001,525,000343,000

Apr 2021

3,992,0001,450,000360,000

May 2021

3,630,0001,353,000347,000

Jun 2021

3,870,0001,354,000389,000

Jul 2021

4,028,0001,423,000341,000

Aug 2021

4,270,0001,385,000378,000

Sep 2021

4,434,0001,375,000410,000

It’s a Small Statistical World

BLS is one of several U.S. statistical agencies that follow consistent policies and share best practices. These agencies also frequently work with their statistical counterparts around the world to develop standards, share information, troubleshoot issues, and improve the quality of available data. At BLS, our Division of International Technical Cooperation coordinates these activities. The division helps to strengthen statistical development by organizing seminars, consultations, and meetings for international visitors with BLS staff. The division also provides BLS input on global statistical initiatives. Without missing a beat, most of these activities moved to virtual platforms during the COVID-19 pandemic. Despite some time-zone challenges, which often lead to early morning or late-night video meetings, BLS continues to play an active role on the world stage.

World map

Today I’m highlighting some recent international engagements, which have included our colleagues from Australia, Canada, France, Greece, Italy, Mexico, South Korea, and the United Kingdom. These events are often mutually beneficial, as they provide opportunities for BLS staff to learn more about the experiences of our international counterparts.

  • BLS staff met with a former Australian Bureau of Statistics official who was working with the U.K. Statistics Authority and the U.K. Office for National Statistics to research best practices in implementing international statistical standards. They discussed the international comparability of domestic industry and product classifications, data quality and publishing, and the independence of statistical organizations.
  • Staff from the Australian Bureau of Statistics are planning to revise their household expenditure survey. They turned to BLS experts, who shared their insights and experiences in improving our Consumer Expenditure Surveys.
  • Staff from the Statistical Division at the United Nations asked BLS to comment on issues surrounding the classification of business functions; household income, consumption, and wealth; and unpaid household service work. Input from staff in multiple offices will inform the BLS response to this request.
  • BLS staff, our counterparts in Canada and Mexico, and colleagues from across Europe and Asia discussed data ethics in a meeting organized by the Centre for Applied Data Ethics at the U.K. Statistics Authority. Country representatives summarized how their organizations assess ethical considerations when producing official statistics. The U.K. Statistics Authority identified the following ethical considerations as being especially important:
Public Good: The use of data has clear benefits for users and serves the public good.
Confidentiality, Data Security: The data subject's identity (whether person or organisation) is protected, information is kept confidential and secure, and the issue of consent is considered appropriately.
Methods and Quality: The risks and limits of new technologies are considered and there is sufficient human oversight so that methods employed are consistent with recognised standards of integrity and quality.
Legal Compliance: Data used and methods employed are consistent with legal requirements.
Public Views and Engagement: The views of the public are considered in light of the data used and the perceived benefits of the research.
Transparency: The access, use and sharing of data is transparent, and is communicated clearly and accessibly to the public.

From its founding, BLS has understood the importance of these issues. Our written policies and strategic plans reflect these principles. They also are reflected in the Foundations for Evidence-Based Policymaking Act and the newly formed Scientific Integrity Task Force, which includes BLS staff among its members.

And that’s just some of what we did this summer! BLS has a longstanding reputation for providing expert training and guidance and participating in international statistical forums. We also provide BLS data to the International Labour Organization and the Organisation for Economic Cooperation and Development, among others. These organizations often feature BLS statistics in their databases. Since its inception, BLS has provided technical assistance to our international counterparts, starting with our first Commissioner, Carroll Wright, who directed BLS staff to advise foreign governments establishing statistical agencies. Commissioner Wright was also a member of several international statistical associations, a tradition that continues today. Currently, BLS staff participate in many international expert groups, including the Voorburg Group on Service Statistics, the Wiesbaden Group on Business Registers, and the International Conference of Labor Statisticians. These groups provide BLS staff with opportunities to discuss topics of common interest, to propose and learn about innovative solutions to data measurement issues, and to influence discussions about important economic concepts.

BLS began providing technical assistance in earnest in the late 1940s as part of the U.S. government’s European Economic Recovery Program. BLS staff planned and conducted productivity studies and helped European governments establish their own economic statistics. Similar efforts continue today for our colleagues around the world, many of whom have participated in our international training programs. While we have temporarily halted in-person training programs because of the pandemic, our staff plan to provide more training modules virtually in response to the popularity of these programs. Over the last 10 years, BLS has provided training or other technical assistance to over 1,700 seminar participants and other visitors from 95 countries. More recently, the International Monetary Fund has asked BLS to provide training on Producer Price Indexes and Import and Export Price Indexes to our colleagues abroad.

I am incredibly grateful to all the subject matter experts throughout BLS who provide invaluable assistance with these activities and help maintain our excellent reputation in the international statistical community. We look forward to your continued support as BLS strengthens important international relationships, virtually for now, and hopefully in person soon.

Paid Leave Benefits When You Are Unable to Work

Many American workers have lost jobs or had their work hours reduced as a result of the COVID-19 pandemic and response efforts. Many other workers still have jobs, but their work environment probably has changed since March. It’s reasonable to assume more people are working from home now than the 29 percent we reported who could work at home in 2017–18. At BLS we are still working to provide you with the latest economic data and analysis, but nearly all of us are now working from home, instead of in our offices.

Still, there are many jobs that just can’t be done from home. In these challenging times, I know we all are grateful for the healthcare workers who are treating patients who have COVID-19 and other medical conditions. We’re grateful for our emergency responders and for the truck drivers, warehouse workers, delivery workers, and staff in grocery stores, pharmacies, and other retail establishments that provide us with the necessities of daily life. As much as I think of these men and women as superheroes, I know they are humans. Even extraordinary humans can get sick, or they may need to take care of family members who get sick. Let’s look at the leave benefits available to them if they need it.

According to our National Compensation Survey, 73 percent of private industry workers were covered by paid sick leave in 2019. Among state and local government workers, 91 percent were covered by paid sick leave. The availability of sick leave benefits varied by occupation, ranging from 94 percent of managers in private industry to 56 percent of workers in construction and extraction occupations.

The share with paid sick leave also varies by industry, pay level, size of establishment, and other characteristics of jobs and employers. The following chart shows sick leave availability for employers of different sizes.

Percent of workers in private industry with access to paid sick leave by establishment size, March 2019

Editor’s note: Data for this chart are available in the table below.

Paid sick leave plans commonly provide a fixed number of days per year. The number of days may vary by the worker’s length of service with the employer. The average in private industry in 2019 was 7 paid sick leave days.

Average number of paid sick leave days per year for workers in private industry, by length of service and establishment size, March 2019

Editor’s note: Data for this chart are available in the table below.

About half of workers with such a plan could carry over unused days from year to year.

We recently posted a new fact sheet on paid sick leave that provides even more detail.

In the past few years, some states and cities have mandated that certain employers provide their workers with paid sick leave. We include these mandated plans in our data on paid leave. A Federal law passed in March 2020 requires paid sick leave for certain workers affected by COVID-19.

In addition to paid sick leave, some employers offer a short-term disability insurance plan when employees can’t work because of illness. These plans are sometimes called sickness and accident insurance plans. This was traditionally a blue-collar or union benefit, and it often replaces only a portion of an employee’s pay. In 2019, 42 percent of private industry workers had access to such a benefit. Like sick leave, the availability of short-term disability benefits varies widely across worker groups. Some states provide Temporary Disability Insurance plans that provide similar benefits.

While the National Compensation Survey asks employers what benefits they offer to workers, the American Time Use Survey recently asked workers whether paid leave is available from their employer and whether they used it. In 2017–18, two-thirds of workers had access to paid leave at their jobs. These data include information on age, sex, and other characteristics. For example, younger workers (ages 15–24) and older workers (age 65 and older) were less likely to have access to paid leave than were other workers.

Percent of workers with access to paid leave by age, 2017–18 averages

Editor’s note: Data for this chart are available in the table below.

While the survey did not ask workers to classify the type of leave, they were asked the reasons they could take leave. Of those with paid leave available, 94 percent could use it for their own illness or medical care, and 78 percent could use it for the illness or medical care of another family member.

I hope you and your loved ones remain healthy and are able to take care of each other in these challenging times. High-quality data will be vital in the public health response to the COVID-19 pandemic. High-quality data also will be vital for measuring the economic impact of the pandemic and recovery from it. My colleagues at BLS and our fellow U.S. statistical agencies remain on the job to provide you with gold standard data.

Percent of workers in private industry with access to paid sick leave by establishment size, March 2019
Establishment sizePercent

1–49 workers

64%

50–99 workers

68

100–499 workers

80

500 workers or more

89
Average number of paid sick leave days per year for workers in private industry, by length of service and establishment size, March 2019
Length of serviceAll establishments 1 to 49 workers50 to 99 workers100 to 499 workers500 workers or more

After 1 year

76678

After 5 years

77679

After 10 years

77779

After 20 years

77779
Percent of workers with access to paid leave by age, 2017–18 averages
AgePercent

Ages 15–24

35.4%

Ages 25–34

70.3

Ages 35–44

71.7

Ages 45–54

74.4

Ages 55–64

74.2

Age 65 and older

51.7

New Data on Balancing Family Needs with Work

Among the many challenges for today’s families is the balance between caregiving and the demands of working outside the home. Some workers are even sandwiched between the need to provide both childcare and eldercare. New information from the Bureau of Labor Statistics shows that about two out of three employees have paid time off available to meet these needs.

Interest among federal, state, and local policymakers in paid time off and other job flexibilities motivated the U.S. Department of Labor’s Women’s Bureau to sponsor an extra set of questions in the American Time Use Survey. The 2017–18 Leave and Job Flexibilities Module gives us data on the characteristics of wage and salary workers who have access to paid and unpaid leave in their jobs. The module also asked questions about workers who work at home and whether they have flexible work schedules. We also know more about workers who do not have access to leave and job flexibilities. Because we collected the data directly from workers, we could ask them about their experiences, such as the reasons they take leave, or don’t take it even when they need to, and why they work at home.

We now know that 66 percent of U.S. wage and salary workers were able to take paid leave from their jobs in 2017–18. Workers were most often able to use paid leave for a vacation and if they were sick or needed medical care. One area of interest is about people who provide unpaid eldercare. The survey showed that 64 percent of eldercare providers who were employed were able to use paid leave to provide elder caregiving. Another 28 percent of these caregivers were not able to take paid leave for this reason, and 8 percent didn’t know if their employer would allow them to use paid leave to provide eldercare.

Percent of workers with access to paid leave who could use it for the following reasons, 2017–18

Editor’s note: Data for this chart are available in the table below.

We also have learned that 36 million workers (25 percent) sometimes worked at home, and they did so for different reasons. Twenty-four percent worked at home because of a personal preference, 23 percent did so to catch up on work, 22 percent worked at home to coordinate their work schedule with personal or family needs, and 16 percent did so because their job required it. Among those who sometimes worked at home, men and women had different reasons for doing so. Women were more likely than men to work at home to finish or catch up on work and to coordinate their work schedule with personal or family needs. Men were more likely than women to work at home because of a personal preference.

Percent of workers who work at home by main reason, 2017–18

Editor’s note: Data for this chart are available in the table below.

We published these results and more in two recent news releases. One news release focused on workers’ access to leave, their use of leave, and an unmet need for leave. The second focused on workers’ job flexibilities and work schedules.

These releases present data on:

  • Access to paid and unpaid time off
  • Use of paid and unpaid time off
  • Needing to take leave from a job but deciding not to take it
  • Flexible work hours
  • Knowing work schedule in advance
  • Working from home

The releases provide information by:

  • Gender
  • Age
  • Race
  • Hispanic or Latino ethnicity
  • Educational attainment
  • Full- or part-time status
  • Earnings

We also have data files that allow researchers to analyze the data and gain even more insights. Following the policies of BLS and the U.S. Census Bureau to protect the privacy of survey respondents, these data files do not have any information that could identify individual participants.

Percent of workers with access to paid leave who could use it for the following reasons, 2017–18
ReasonYesNoDon’t know

Vacation

95%5%0%

Own illness or medical care

9461

Illness or medical care of another family member

78166

Birth or adoption of a child

76159

Errands or personal reasons

70282

Childcare, other than for illness

65314

Eldercare

64288

Note: The estimates for “childcare, other than for illness” are for workers who were parents of household children under age 18. The estimates for “eldercare” are only for workers who were eldercare providers.

Percent of workers who work at home by main reason, 2017–18
ReasonTotalMenWomen

Personal preference

24%27%21%

Finish or catch up on work

232126

Coordinate work schedule with personal or family needs

222025

Job requires working at home

161616

Reduce commuting time or expense

9109

Weather

443

Other

221

Baseball, Hot Dogs, and Statistics

Summer is in full swing, which means that when I’m not talking about BLS data, I’m talking about baseball, something I could do full time. Luckily these two topics have a lot in common; nothing quite says statistics in the summertime like baseball does. We fans have followed baseball statistics for nearly as long as the game has been played. Teams today increasingly use statistics—or “analytics”—to decide which players to add to their rosters, who to play in any game situation, and even where to position fielders for certain batters. That’s a lot like the innovations BLS and the other federal statistical agencies focus on to help people make informed decisions for their families, businesses, and the broader economy.

I grew up a St. Louis Cardinals fan until the mid-1960s, when the lamentable Kansas City Athletics moved to Oakland and the American League expansion team, Kansas City Royals, brought winning baseball to Kansas. I had a second home, as it were, in the seats of Kauffman Stadium, or “The K” to us Kansas City Royals fans. Today I cheer for the Washington Nationals, having lived in the D.C. area for the past 25 years. Regardless of your favorite team, if you’re a baseball fan you know statistics are a huge part of how your team performs. While I could talk about George Brett’s batting average, home runs, or wins above replacement, let’s instead look at where America’s agency on labor data meets America’s favorite pastime.

Spectator sports employed over 144,000 workers in 2018. The map below shows the metropolitan areas with the most jobs in spectator sports. The New York-Newark-Jersey City, NY-NJ-PA metro area, home of the Yankees and Mets, employs the most people at 8,674. Spectator sports include all professional and semi-professional sport teams.

Employment in spectator sports by metropolitan area, 2018

Editor’s note: Data for this map are available in the table below.

Also consider the Occupational Employment Statistics program. In 2018, there were 27,780 radio and television announcers and 7,480 public address announcers. There were also 236,970 coaches and scouts and 19,090 umpires and referees in 2018.

Here’s a look at some of the occupations within the spectator sports industry:

Employment in selected occupations in the spectator sports industry, May 2018

Editor’s note: Data for this chart are available in the table below.

If you’re going to the game, the Consumer Price Index can tell you how prices have changed over time. For example, ticket prices for sporting events decreased 0.8 percent from June 2018 to June 2019. Over the same period, parking fees and tolls increased 3.2 percent and prices for food away from home increased 3.1 percent. At the low end of the increases is beer away from home—a modest 0.8 increase over the year.

Or maybe you just decide to enjoy the game in front of your new 80-inch flat screen TV. You aren’t alone. According to the American Time Use Survey, Americans spend, on average, 2.84 hours a day watching television in 2017. That’s almost enough time to watch your typical 9-inning baseball game.

Can we squeeze any more baseball out of BLS statistics? There’s wage data for ushers, occupational injuries for umpires, and productivity in certain recreation industries. But we’ll save that for another day. For now, sit back and enjoy the game. Play Ball!

Employment in spectator sports by metropolitan area, 2018
Metropolitan area Employment
Abilene, TX 14
Akron, OH 215
Albany-Schenectady-Troy, NY 537
Albuquerque, NM 241
Anchorage, AK 204
Ann Arbor, MI 84
Atlanta-Sandy Springs-Roswell, GA 1,948
Augusta-Richmond County, GA-SC 314
Austin-Round Rock, TX 1,071
Bakersfield, CA 229
Baltimore-Columbia-Towson, MD 1,872
Bangor, ME 32
Barnstable Town, MA 9
Baton Rouge, LA 15
Beaumont-Port Arthur, TX 5
Billings, MT 78
Birmingham-Hoover, AL 372
Bloomington, IL 54
Boulder, CO 22
Bridgeport-Stamford-Norwalk, CT 83
Burlington-South Burlington, VT 92
Canton-Massillon, OH 13
Cape Coral-Fort Myers, FL 718
Charleston, WV 118
Charleston-North Charleston, SC 256
Charlotte-Concord-Gastonia, NC-SC 6,081
Chicago-Naperville-Elgin, IL-IN-WI 4,763
Cincinnati, OH-KY-IN 1,473
Cleveland-Elyria, OH 2,019
Coeur d’Alene, ID 36
College Station-Bryan, TX 20
Colorado Springs, CO 214
Columbia, SC 383
Columbus, OH 813
Corpus Christi, TX 153
Dallas-Fort Worth-Arlington, TX 3,392
Deltona-Daytona Beach-Ormond Beach, FL 1,294
Denver-Aurora-Lakewood, CO 999
Des Moines-West Des Moines, IA 375
Detroit-Warren-Dearborn, MI 1,682
Dover, DE 222
Dubuque, IA 72
Duluth, MN-WI 75
El Paso, TX 269
Erie, PA 105
Eugene, OR 67
Evansville, IN-KY 209
Fairbanks, AK 29
Flint, MI 6
Florence, SC 43
Fort Collins, CO 4
Fresno, CA 542
Grand Junction, CO 67
Grand Rapids-Wyoming, MI 234
Great Falls, MT 72
Greeley, CO 96
Greenville, NC 54
Greenville-Anderson-Mauldin, SC 234
Gulfport-Biloxi-Pascagoula, MS 121
Hagerstown-Martinsburg, MD-WV 21
Harrisburg-Carlisle, PA 316
Hartford-West Hartford-East Hartford, CT 233
Hickory-Lenoir-Morganton, NC 111
Hot Springs, AR 665
Houston-The Woodlands-Sugar Land, TX 2,968
Huntington-Ashland, WV-KY-OH 27
Huntsville, AL 47
Indianapolis-Carmel-Anderson, IN 2,786
Jacksonville, FL 1,397
Janesville-Beloit, WI 52
Joplin, MO 11
Kahului-Wailuku-Lahaina, HI 3
Kansas City, MO-KS 1,737
Kennewick-Richland, WA 84
Lake Charles, LA 11
Lakeland-Winter Haven, FL 387
Lancaster, PA 160
Las Cruces, NM 18
Las Vegas-Henderson-Paradise, NV 835
Lebanon, PA 16
Lexington-Fayette, KY 1,556
Lincoln, NE 172
Little Rock-North Little Rock-Conway, AR 148
Los Angeles-Long Beach-Anaheim, CA 7,100
Louisville-Jefferson County, KY-IN 1,337
Lubbock, TX 12
Manchester-Nashua, NH 144
Medford, OR 23
Memphis, TN-MS-AR 1,349
Miami-Fort Lauderdale-West Palm Beach, FL 6,476
Midland, TX 99
Milwaukee-Waukesha-West Allis, WI 2,218
Minneapolis-St. Paul-Bloomington, MN-WI 3,337
Missoula, MT 20
Mobile, AL 79
Myrtle Beach-Conway-North Myrtle Beach, SC-NC 171
Naples-Immokalee-Marco Island, FL 23
Nashville-Davidson–Murfreesboro–Franklin, TN 721
New Orleans-Metairie, LA 1,522
New York-Newark-Jersey City, NY-NJ-PA 8,674
North Port-Sarasota-Bradenton, FL 549
Norwich-New London, CT 85
Ocala, FL 490
Ogden-Clearfield, UT 120
Oklahoma City, OK 1,227
Oxnard-Thousand Oaks-Ventura, CA 82
Palm Bay-Melbourne-Titusville, FL 301
Phoenix-Mesa-Scottsdale, AZ 4,398
Pittsburgh, PA 1,603
Pittsfield, MA 21
Portland-South Portland, ME 317
Portland-Vancouver-Hillsboro, OR-WA 1,042
Providence-Warwick, RI-MA 348
Raleigh, NC 1,339
Reading, PA 198
Richmond, VA 381
Riverside-San Bernardino-Ontario, CA 688
Roanoke, VA 98
Rochester, NY 676
Sacramento–Roseville–Arden-Arcade, CA 957
Salem, OR 56
Salisbury, MD-DE 138
San Antonio-New Braunfels, TX 757
San Diego-Carlsbad, CA 1,720
Santa Rosa, CA 223
Seattle-Tacoma-Bellevue, WA 3,176
Sherman-Denison, TX 6
Sioux Falls, SD 138
Spartanburg, SC 15
Spokane-Spokane Valley, WA 209
St. George, UT 20
St. Joseph, MO-KS 13
St. Louis, MO-IL 1,608
State College, PA 75
Stockton-Lodi, CA 130
Tampa-St. Petersburg-Clearwater, FL 3,302
Trenton, NJ 159
Tucson, AZ 83
Tulsa, OK 281
Virginia Beach-Norfolk-Newport News, VA-NC 148
Washington-Arlington-Alexandria, DC-VA-MD-WV 2,931
Waterloo-Cedar Falls, IA 65
Watertown-Fort Drum, NY 15
Wausau, WI 34
Weirton-Steubenville, WV-OH 18
Wheeling, WV-OH 47
Winston-Salem, NC 414
Worcester, MA-CT 97
Yakima, WA 21
York-Hanover, PA 156
Youngstown-Warren-Boardman, OH-PA 84
Yuba City, CA 34
Employment in selected occupations in the spectator sports industry, May 2018
Occupation Employment
Security guards 8,490
Ushers 7,610
Food and beverage servers 6,980
Groundskeepers 2,350
Parking lot attendants 1,850